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How to use to_numpy_dtype method in pandera
Best Python code snippet using pandera_python
test_coretypes.py
Source:test_coretypes.py 
...49 with pytest.raises(TypeError):50 DataShape('5 * int32')51class TestToNumpyDtype(object):52 def test_simple(self):53 assert to_numpy_dtype(dshape('2 * int32')) == np.int3254 assert (to_numpy_dtype(dshape('2 * {x: int32, y: int32}')) ==55 np.dtype([('x', '<i4'), ('y', '<i4')]))56 def test_datetime(self):57 assert to_numpy_dtype(dshape('2 * datetime')) == np.dtype('M8[us]')58 def test_date(self):59 assert to_numpy_dtype(dshape('2 * date')) == np.dtype('M8[D]')60 def test_string(self):61 assert to_numpy_dtype(dshape('2 * string')) == np.dtype('O')62 def test_dimensions(self):63 return to_numpy_dtype(dshape('var * int32')) == np.int3264 def test_timedelta(self):65 assert to_numpy_dtype(dshape('2 * timedelta')) == np.dtype('m8[us]')66 assert to_numpy_dtype(dshape("2 * timedelta[unit='s']")) == \67 np.dtype('m8[s]')68 def test_decimal(self):69 assert to_numpy_dtype(dshape('decimal[18,0]')) == np.int6470 assert to_numpy_dtype(dshape('decimal[7,2]')) == np.float6471 assert to_numpy_dtype(dshape('decimal[4]')) == np.int1672 with pytest.raises(TypeError):73 to_numpy_dtype(dshape('decimal[21]'))74def test_timedelta_eval_repr():75 assert eval(repr(dshape('timedelta'))) == dshape('timedelta')76 assert eval(repr(dshape('timedelta[unit="ms"]'))) == \77 dshape('timedelta[unit="ms"]')78def test_timedelta_bad_unit():79 with pytest.raises(ValueError):80 dshape('timedelta[unit="foo"]')81def test_timedelta_nano():82 dshape('timedelta[unit="ns"]').measure.unit == 'ns'83def test_timedelta_aliases():84 for alias in _unit_aliases:85 a = alias + 's'86 assert (dshape('timedelta[unit=%r]' % a) ==87 dshape('timedelta[unit=%r]' % _unit_aliases[alias]))88class TestFromNumPyDtype(object):89 def test_int32(self):90 assert from_numpy((2,), 'int32') == dshape('2 * int32')91 assert from_numpy((2,), 'i4') == dshape('2 * int32')92 def test_struct(self):93 dtype = np.dtype([('x', '<i4'), ('y', '<i4')])94 result = from_numpy((2,), dtype)95 assert result == dshape('2 * {x: int32, y: int32}')96 def test_datetime(self):97 keys = 'h', 'm', 's', 'ms', 'us', 'ns', 'ps', 'fs', 'as'98 for k in keys:99 assert from_numpy((2,),100 np.dtype('M8[%s]' % k)) == dshape('2 * datetime')101 def test_date(self):102 for d in ('D', 'M', 'Y', 'W'):103 assert from_numpy((2,),104 np.dtype('M8[%s]' % d)) == dshape('2 * date')105 def test_timedelta(self):106 for d in _units:107 assert from_numpy((2,),108 np.dtype('m8[%s]' % d)) == \109 dshape('2 * timedelta[unit=%r]' % d)110 def test_ascii_string(self):111 assert (from_numpy((2,), np.dtype('S7')) ==112 dshape('2 * string[7, "ascii"]'))113 def test_string(self):114 assert (from_numpy((2,), np.dtype('U7')) ==115 dshape('2 * string[7, "U32"]'))116 def test_string_from_CType_classmethod(self):117 assert CType.from_numpy_dtype(np.dtype('S7')) == String(7, 'A')118def test_eq():119 assert dshape('int') == dshape('int')120 assert dshape('int') != 'apple'121def test_serializable():122 ds = dshape('''{id: int64,123 name: string,124 amount: float32,125 arr: 3 * (int32, string)}''')126 ds2 = pickle.loads(pickle.dumps(ds))127 assert str(ds) == str(ds2)128def test_subshape():129 ds = dshape('5 * 3 * float32')130 assert ds.subshape[2:] == dshape('3 * 3 * float32')131 ds = dshape('5 * 3 * float32')132 assert ds.subshape[::2] == dshape('3 * 3 * float32')133def test_negative_slicing():134 ds = dshape('10 * int')135 assert ds.subshape[-3:] == dshape('3 * int')136def test_newaxis_slicing():137 ds = dshape('10 * int')138 assert ds.subshape[None, :] == dshape('1 * 10 * int')139 assert ds.subshape[:, None] == dshape('10 * 1 * int')140def test_datashape_coerces_ints():141 assert DataShape(5, 'int32')[0] == Fixed(5)142 assert DataShape(5, 'int32')[1] == int32143def test_shape():144 assert dshape('5 * 3 * float32').shape == (5, 3)145 assert dshape('float32').shape == ()146 assert dshape('float32').measure.shape == ()147 assert dshape('?float32').measure.shape == ()148def test_option_sanitizes_strings():149 assert Option('float32').ty == dshape('float32').measure150def test_option_passes_itemsize():151 assert (dshape('?float32').measure.itemsize ==152 dshape('float32').measure.itemsize)153class TestComplexFieldNames(object):154 """155 The tests in this class should verify that the datashape parser can handle156 field names that contain strange characters like spaces, quotes, and157 backslashes158 The idea is that any given input datashape should be recoverable once we159 have created the actual dshape object.160 This test suite is by no means complete, but it does handle some of the161 more common special cases (common special? oxymoron?)162 """163 def test_spaces_01(self):164 space_dshape = "{'Unique Key': ?int64}"165 assert space_dshape == str(dshape(space_dshape))166 def test_spaces_02(self):167 big_space_dshape = """{ 'Unique Key' : ?int64, 'Created Date' : string,168'Closed Date' : string, Agency : string, 'Agency Name' : string,169'Complaint Type' : string, Descriptor : string, 'Location Type' : string,170'Incident Zip' : ?int64, 'Incident Address' : ?string, 'Street Name' : ?string,171'Cross Street 1' : ?string, 'Cross Street 2' : ?string,172'Intersection Street 1' : ?string, 'Intersection Street 2' : ?string,173'Address Type' : string, City : string, Landmark : string,174'Facility Type' : string, Status : string, 'Due Date' : string,175'Resolution Action Updated Date' : string, 'Community Board' : string,176Borough : string, 'X Coordinate (State Plane)' : ?int64,177'Y Coordinate (State Plane)' : ?int64, 'Park Facility Name' : string,178'Park Borough' : string, 'School Name' : string, 'School Number' : string,179'School Region' : string, 'School Code' : string,180'School Phone Number' : string, 'School Address' : string,181'School City' : string, 'School State' : string, 'School Zip' : string,182'School Not Found' : string, 'School or Citywide Complaint' : string,183'Vehicle Type' : string, 'Taxi Company Borough' : string,184'Taxi Pick Up Location' : string, 'Bridge Highway Name' : string,185'Bridge Highway Direction' : string, 'Road Ramp' : string,186'Bridge Highway Segment' : string, 'Garage Lot Name' : string,187'Ferry Direction' : string, 'Ferry Terminal Name' : string,188Latitude : ?float64, Longitude : ?float64, Location : string }"""189 ds1 = dshape(big_space_dshape)190 ds2 = dshape(str(ds1))191 assert str(ds1) == str(ds2)192 def test_single_quotes_01(self):193 quotes_dshape = """{ 'field \\' with \\' quotes' : string }"""194 ds1 = dshape(quotes_dshape)195 ds2 = dshape(str(ds1))196 assert str(ds1) == str(ds2)197 def test_double_quotes_01(self):198 quotes_dshape = """{ 'doublequote \" field \"' : int64 }"""199 ds1 = dshape(quotes_dshape)200 ds2 = dshape(str(ds1))201 assert str(ds1) == str(ds2)202 def test_multi_quotes_01(self):203 quotes_dshape = """{204 'field \\' with \\' quotes' : string,205 'doublequote \" field \"' : int64206 }"""207 ds1 = dshape(quotes_dshape)208 ds2 = dshape(str(ds1))209 assert str(ds1) == str(ds2)210 def test_mixed_quotes_01(self):211 quotes_dshape = """{212 'field \" with \\' quotes' : string,213 'doublequote \" field \\'' : int64214 }"""215 ds1 = dshape(quotes_dshape)216 ds2 = dshape(str(ds1))217 assert str(ds1) == str(ds2)218 def test_bad_02(self):219 bad_dshape = """{ Unique Key : int64}"""220 with pytest.raises(error.DataShapeSyntaxError):221 dshape(bad_dshape)222 def test_bad_backslashes_01(self):223 """backslashes aren't allowed in datashapes according to the definitions224 in lexer.py as of 2014-10-02. This is probably an oversight that should225 be fixed.226 """227 backslash_dshape = """{ 'field with \\\\ backslashes' : int64 }"""228 with pytest.raises(error.DataShapeSyntaxError):229 dshape(backslash_dshape)230def test_record_string():231 s = '{name_with_underscores: int32}'232 assert s.replace(' ', '') == str(dshape(s)).replace(' ', '')233def test_record_with_unicode_name_as_numpy_dtype():234 r = Record([(unicode('a'), 'int32')])235 assert r.to_numpy_dtype() == np.dtype([('a', 'i4')])236@pytest.mark.xfail(237 sys.version_info < (2, 7),238 reason='OrderedDict not supported before 2.7',239)240def test_record_from_OrderedDict():241 r = Record(OrderedDict([('a', 'int32'), ('b', 'float64')]))242 assert r.to_numpy_dtype() == np.dtype([('a', 'i4'), ('b', 'f8')])243def test_tuple_datashape_to_numpy_dtype():244 ds = dshape('5 * (int32, float32)')245 assert to_numpy_dtype(ds) == [('f0', 'i4'), ('f1', 'f4')]246def test_option_date_to_numpy():247 assert Option(Date()).to_numpy_dtype() == np.dtype('datetime64[D]')248def test_option_datetime_to_numpy():249 assert Option(DateTime()).to_numpy_dtype() == np.dtype('datetime64[us]')250@pytest.mark.parametrize('unit',251 ['Y', 'M', 'D', 'h', 'm', 's', 'ms', 'us', 'ns'])252def test_option_timedelta_to_numpy(unit):253 assert (Option(TimeDelta(unit=unit)).to_numpy_dtype() ==254 np.dtype('timedelta64[%s]' % unit))255def unique(x):256 seen = set()257 for el in x:258 if el not in seen:259 yield el260 seen.add(el)261@pytest.mark.parametrize('data', [list('aaaabbbccc'), [-1, 2, 3, 4, 4, 3, 5]])262def test_categorical(data):263 c = Categorical(tuple(unique(data)))264 assert list(unique(c.categories)) == list(unique(data))265 assert str(c) == 'categorical[[%s], type=%s, ordered=False]' % (266 ', '.join(map(repr, c.categories)), c.type267 )268 assert (269 repr(c) == 'Categorical(categories=[%s], type=%r, ordered=False)' % (270 ', '.join(map(repr, c.categories)), c.type271 )272 )273 assert (274 dshape("categorical[[%s], type=%s, ordered=False]" % (275 ', '.join(map(repr, c.categories)), c.type276 )) == DataShape(c)277 )278 assert (279 dshape("categorical[[%s], type=%s, ordered=False]" % (280 ', '.join(map(repr, c.categories)), c.type281 )) == DataShape(c)282 )283def test_long_categorical_repr():284 cats = list('abcdefghijklmnopqrstuvwxyz')285 c = Categorical(cats, ordered=True)286 assert str(c) == 'categorical[[%s, ...], type=%s, ordered=True]' % (287 ', '.join(map(repr, cats[:10])),288 c.type289 )290def test_duplicate_field_names_fails():291 fields = [('a', 'int32'), ('b', 'string'), ('a', 'float32')]292 with pytest.raises(ValueError):293 Record(fields)294@pytest.mark.parametrize('ds',295 ['int64',296 'var * float64',297 '10 * var * int16',298 '{a: int32, b: ?string}',299 'var * {a: int32, b: ?string}',300 '10 * {a: ?int32, b: var * {c: string[30]}}',301 '{"weird col": 3 * var * 2 * ?{a: int8, b: ?uint8}}',302 'var * {"func-y": (A) -> var * {a: 10 * float64}}',303 'decimal[18]',304 'var * {amount: ?decimal[9,2]}'])305def test_repr_of_eval_is_dshape(ds):306 assert eval(repr(dshape(ds))) == dshape(ds)307def test_complex_with_real_component_fails():308 with pytest.raises(TypeError):309 dshape('complex[int64]')310def test_already_registered_type():311 with pytest.raises(TypeError):312 Type.register('int64', int64)313def test_multiplication_of_dshapes():314 with pytest.raises(TypeError):315 int32 * 10316def test_ellipsis_with_typevar_repr():317 assert str(Ellipsis(typevar=TypeVar('T'))) == 'T...'318 assert repr(Ellipsis(typevar=TypeVar('T'))) == 'Ellipsis(\'T...\')'319def test_null_datashape_string():320 assert str(null) == 'null'321@pytest.mark.xfail(raises=TypeError, reason="Not yet implemented")322def test_time_with_tz_not_a_string():323 assert Time(tz=datetime.tzinfo())324@pytest.mark.xfail(raises=TypeError, reason="Not yet implemented")325def test_datetime_with_tz_not_a_string():326 assert DateTime(tz=datetime.tzinfo())327@pytest.mark.parametrize('unit', _units)328def test_timedelta_repr(unit):329 assert repr(TimeDelta(unit=unit)) == 'TimeDelta(unit=%r)' % unit330@pytest.mark.parametrize('unit', _units)331def test_timedelta_str(unit):332 assert str(TimeDelta(unit=unit)) == 'timedelta[unit=%r]' % unit333def test_unit_construction():334 with pytest.raises(TypeError):335 Units(1)336 with pytest.raises(TypeError):337 Units('kg', 1)338def test_unit_str():339 assert str(Units('kg')) == "units['kg']"340 assert (str(Units('counts/time', DataShape(uint32))) ==341 "units['counts/time', uint32]")342def test_bytes_str():343 assert str(Bytes()) == 'bytes'344def test_unsupported_string_encoding():345 with pytest.raises(ValueError):346 String(1, 'asdfasdf')347def test_all_dims_before_last():348 with pytest.raises(TypeError):349 DataShape(uint32, var, uint32)350def test_datashape_parameter_count():351 with pytest.raises(ValueError):352 DataShape()353def test_named_datashape():354 assert str(DataShape(uint32, name='myuint')) == 'myuint'355def test_subarray_invalid_index():356 with pytest.raises(IndexError):357 dshape('1 * 2 * 3 * int32').subarray(42)358def test_record_subshape_integer_index():359 ds = DataShape(Record([('a', 'int32')]))360 assert ds.subshape[0] == int32361def test_slice_subshape_negative_step():362 ds = 30 * Record([('a', 'int32')])363 assert ds.subshape[:-1] == 29 * Record([('a', 'int32')])364def test_slice_subshape_negative_start():365 ds = var * Record([('a', 'int32')])366 assert ds.subshape[-1:] == var * Record([('a', 'int32')])367def test_slice_subshape_bad_types():368 ds = var * Record([('a', 'int32')])369 with pytest.raises(TypeError):370 assert ds.subshape[1.0]371@pytest.mark.parametrize(['base', 'expected'],372 zip([timedelta_, date_, datetime_],373 ['timedelta64[us]', 'datetime64[D]',374 'datetime64[us]']))375def test_option_to_numpy_dtype(base, expected):376 assert Option(base).to_numpy_dtype() == np.dtype(expected)377@pytest.mark.xfail(raises=TypeError,378 reason=('NumPy has no notion of missing for types other '379 'than timedelta, datetime, and date'))380@pytest.mark.parametrize('base', [int32, float64, Record([('a', uint32)])])381def test_option_to_numpy_dtype_fails(base):382 Option(base).to_numpy_dtype()383@pytest.mark.xfail(raises=NotImplementedError,384 reason='DataShape does not know about void types (yet?)')385def test_from_numpy_dtype_fails():386 x = np.zeros(2, np.dtype([('a', 'int32')]))387 CType.from_numpy_dtype(x[0].dtype)388def test_ctype_alignment():389 assert int32.alignment == 4390def test_fixed_dimensions_must_be_positive():391 with pytest.raises(ValueError):392 Fixed(-1)393def test_fixed_comparison():394 assert Fixed(1) != 'a'395def test_typevar_must_be_upper_case():396 with pytest.raises(ValueError):397 TypeVar('t')398def test_typevar_repr():399 assert repr(TypeVar('T')) == "TypeVar(symbol='T')"400def test_funcproto_attrs():401 f = dshape('(int32, ?float64) -> {a: ?string}').measure402 assert f.restype == DataShape(Record([('a', Option(String()))]))403 assert f.argtypes == (DataShape(int32), DataShape(Option(float64)))404def test_tuple_str():405 assert str(Tuple([Option(int32), float64])) == '(?int32, float64)'406def test_to_numpy_fails():407 ds = var * int32408 with pytest.raises(TypeError):409 to_numpy(ds)410 with pytest.raises(TypeError):411 to_numpy(Option(int32))412def test_map():413 fk = Map(int32, Record([('a', int32)]))414 assert fk.key == int32415 assert fk.value == Record([('a', int32)])416 assert fk.value.dict == {'a': int32}417 assert fk.value.fields == (('a', int32),)418 with pytest.raises(TypeError):419 fk.to_numpy_dtype()420def test_map_parse():421 result = dshape("var * {b: map[int32, {a: int64}]}")422 recmeasure = Map(dshape(int32), DataShape(Record([('a', int64)])))423 assert result == DataShape(var, Record([('b', recmeasure)]))424def test_decimal_attributes():425 d1 = Decimal(18)426 assert d1.precision == 18 and d1.scale == 0427 d2 = Decimal(4, 0)428 assert d2.precision == 4 and d2.scale == 0429 d3 = Decimal(11, 2)430 assert d3.precision == 11 and d3.scale == 2431 with pytest.raises(TypeError):432 Decimal()433def test_record_literal():...
test_nns.py
Source:test_nns.py
...80@pytest.mark.parametrize("dtype", list_float_dtypes())81@pytest.mark.parametrize("device", list_devices())82def test_knn_setup(benchmark, size, dim, dtype, device):83 nns_opt = dict(knn=1, radius=0.01)84 np_a = np.array(np.random.rand(size, dim), dtype=to_numpy_dtype(dtype))85 a = o3c.Tensor(np_a, dtype=dtype, device=device)86 benchmark(NNSOps.knn_setup, a, nns_opt)87@pytest.mark.parametrize("size", list_sizes())88@pytest.mark.parametrize("dim", list_dimensions())89@pytest.mark.parametrize("dtype", list_float_dtypes())90@pytest.mark.parametrize("device", list_devices())91def test_knn_search(benchmark, size, dim, dtype, device):92 nns_opt = dict(knn=1, radius=0.01)93 np_a = np.array(np.random.rand(size, dim), dtype=to_numpy_dtype(dtype))94 np_b = np.array(np.random.rand(size, dim), dtype=to_numpy_dtype(dtype))95 a = o3c.Tensor(np_a, dtype=dtype, device=device)96 b = o3c.Tensor(np_b, dtype=dtype, device=device)97 index = NNSOps.knn_setup(a, nns_opt)98 benchmark(NNSOps.knn_search, index, b, nns_opt)99@pytest.mark.parametrize("size", list_sizes())100@pytest.mark.parametrize("dtype", list_float_dtypes())101@pytest.mark.parametrize("device", list_devices())102def test_radius_setup(benchmark, size, dtype, device):103 nns_opt = dict(knn=1, radius=0.01)104 np_a = np.array(np.random.rand(size, 3), dtype=to_numpy_dtype(dtype))105 a = o3c.Tensor(np_a, dtype=dtype, device=device)106 benchmark(NNSOps.radius_setup, a, nns_opt)107@pytest.mark.parametrize("size", list_sizes())108@pytest.mark.parametrize("dtype", list_float_dtypes())109@pytest.mark.parametrize("device", list_devices())110def test_radius_search(benchmark, size, dtype, device):111 nns_opt = dict(knn=1, radius=0.01)112 np_a = np.array(np.random.rand(size, 3), dtype=to_numpy_dtype(dtype))113 np_b = np.array(np.random.rand(size, 3), dtype=to_numpy_dtype(dtype))114 a = o3c.Tensor(np_a, dtype=dtype, device=device)115 b = o3c.Tensor(np_b, dtype=dtype, device=device)116 index = NNSOps.radius_setup(a, nns_opt)117 benchmark(NNSOps.radius_search, index, b, nns_opt)118@pytest.mark.parametrize("size", list_sizes())119@pytest.mark.parametrize("dtype", list_float_dtypes())120@pytest.mark.parametrize("device", list_devices())121def test_hybrid_setup(benchmark, size, dtype, device):122 nns_opt = dict(knn=1, radius=0.01)123 np_a = np.array(np.random.rand(size, 3), dtype=to_numpy_dtype(dtype))124 a = o3c.Tensor(np_a, dtype=dtype, device=device)125 benchmark(NNSOps.hybrid_setup, a, nns_opt)126@pytest.mark.parametrize("size", list_sizes())127@pytest.mark.parametrize("dtype", list_float_dtypes())128@pytest.mark.parametrize("device", list_devices())129def test_hybrid_search(benchmark, size, dtype, device):130 nns_opt = dict(knn=1, radius=0.01)131 np_a = np.array(np.random.rand(size, 3), dtype=to_numpy_dtype(dtype))132 np_b = np.array(np.random.rand(size, 3), dtype=to_numpy_dtype(dtype))133 a = o3c.Tensor(np_a, dtype=dtype, device=device)134 b = o3c.Tensor(np_b, dtype=dtype, device=device)135 index = NNSOps.hybrid_setup(a, nns_opt)...
test_types.py
Source:test_types.py
...8 def test_ints(self):9 types = ['int8', 'int16', 'int32', 'int64']10 for type_ in types:11 a = blaze.array(np.arange(3), dshape=type_)12 dtype = to_numpy_dtype(a.dshape)13 self.assertEqual(dtype, np.dtype(type_))14 self.assertEqual(ddesc_as_py(a.ddesc), [0, 1, 2])15 def test_uints(self):16 types = ['uint8', 'uint16', 'uint32', 'uint64']17 for type_ in types:18 a = blaze.array(np.arange(3), dshape=type_)19 dtype = to_numpy_dtype(a.dshape)20 self.assertEqual(dtype, np.dtype(type_))21 self.assertEqual(ddesc_as_py(a.ddesc), [0, 1, 2])22 def test_floats(self):23 #types = ['float16', 'float32', 'float64']24 types = ['float32', 'float64']25 for type_ in types:26 a = blaze.array(np.arange(3), dshape=type_)27 dtype = to_numpy_dtype(a.dshape)28 self.assertEqual(dtype, np.dtype(type_))29 if type_ != 'float16':30 # ddesc_as_py does not support this yet31 self.assertEqual(ddesc_as_py(a.ddesc), [0, 1, 2])32 def test_complex(self):33 types = ['complex64', 'complex128']34 for type_ in types:35 a = blaze.array(np.arange(3), dshape=type_)36 dtype = to_numpy_dtype(a.dshape)37 self.assertEqual(dtype, np.dtype(type_))38 # ddesc_as_py does not support complexes yet.....
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